Munich, Germany-based Brainlab has officially rolled out Loop-X, the first mobile intraoperative imaging robot for spine surgery.
Brainlab Rolls Out Mobile Intraoperative Imaging Robot, Literally!
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According to Brainlab, “The Loop-X imaging robot integrates with Brainlab Elements software as well as Kick and Curve Navigation and functions with Cirq and Quentry, maximizing interoperability and data enrichment while contributing to increased surgical confidence.”
The Loop-X, says the company, “offers smart integration with navigation, enabling the surgeon to use a pointer for on-the-fly definition of the region of interest. Moreover, pre-planned trajectories can be used for aligning the imaging system in line to the trajectory, using gantry tilt and jaw. Loop-X is next-gen technology in terms of size, collaborative robotic functionalities and navigation integration capabilities.”
“Loop-X is a critical milestone in contributing disruptive innovations in spinal surgery,” said Stefan Vilsmeier, company president and CEO. “It provides us with an even stronger foundation for leveraging emerging technologies such as AI [artificial intelligence], big data, cloud computing, augmented reality and spatial computing.”
Furthermore, says Brainlab, the “Loop-X imaging robot builds on the broad utility of X-ray-based 2D and 3D imaging in the O.R..” The company is hoping to provide hospitals and clinics with a surgery-centric digital platform for every surgery. The Brainlab system, says the company, “goes beyond simple diagnostic imaging to intelligently capturing partial information and then ‘digitizing’ anatomical intraoperative changes. According the Brainlab, that “updates a “digital model” of the patient previously generated by aggregating pre-operative images.”
The Loop-X imaging robot was actually developed by Salzburg, Germany-based medPhoton in close partnership with Brainlab. Brainlab is both an exclusive distributor of Loop-X and an investor in medPhoton.
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This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?
Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.
We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.
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